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WIP Summary of Davies 2017 article from special Theory Culture and Society issue on Elites and Power after Financialization
Elite Power under Advanced Neoliberalism
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Disparities in Birth outcomes Dynamic Map
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Causal loop diagram illustrating a variety of feedback loops influencing the price of oil.
Oil Price Influencers (3-Loop)
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Book summary of Albert O Hirschman's 1982 book, explaining cycles of collective public action.
Shifting involvements
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Introduction:
This simulation model demonstrates the outbreak of Covid-19 in Burnie, Tasmania and how the corresponding government’s responses affect the spreading of Covid-19. Meanwhile, this model also shows how the economy in Burnie is influenced by the impacts of both Covid-19 and government policies.

Variables: 
This simulation contains some relevant variables as follow:

Variables in Covid-19 outbreaks: (1) Infection rate, (2) Recovery rate, (3) Death rate, (4) Immunity loss rate

Variables in Government policies: (1) Vaccination rate, (2) Lockdown, (3) Travel ban, (4)Quarantine

Variables in Economy: (1) E-commerce business, (2) Unemployment rate, (3) Economic growth rate.

Assumption:
Government responses would be triggered when reported Covid-19 cases are at least 10.

The government policies reduce the spreading of Covid-19, but they would also limit economic development at the same time due to the negative impact of the policies on the economy is greater than the positive impact.

The increase in reported Covid-19 cases would negatively affect economic growth.

Interesting Insights:
The first finding is that the death number would keep increasing even though the infection rate has decreased, but with stronger government policies (such as implementing a coefficient over 25%), no more death numbers will occur caused by Covid-19.

The second finding is that as government policies limit business activities, with the increasing number of reported Covid-19 cases, economic growth will suffer a severe blow even if e-commerce grows, it can’t make up for this economic loss.
BMA 708 assignment 3 - simulation model of Covid-19 Outbreak in Burnie, Tasmania
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This causal loop diagram illustrates the interconnected factors affecting the economic empowerment of Congolese refugee women in Rwanda, with economic dependency as the central problem reinforced by limited access to vocational training, employment opportunities, and financial services. The diagram shows two key reinforcing loops: one where vocational training leads to employment and income generation, which reduces dependency and improves access to further training (R1), and another where income generation builds self-confidence and skills recognition, leading to better employment opportunities (R2), while language barriers and cultural constraints act as inhibiting factors throughout the system.

Causal Loop Diagram: Economic Empowerment of Congolese refugee women in Rwanda.
8 months ago
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About the Model 
This model is a dynamic model which explains the relationship between the police of the government and the economy situation in Burnie Tasmania after the outbreak of Corona Virus.

This model is based on SIR model, which explains the dynamic reflection between the people who were susceptible, infected,deaths and recovered. 

Assumptions 
This model assumes that when the Covid-19 positive is equal or bigger than 10, the government policy can be triggered. This model assumes that the shopping rate in retail shops and the dining rates in the restaurants can only be influenced by the government policy.

Interesting Insights  

The government police can have negative influence on the infection process, as it reduced the possibility of people get infected in the public environments. The government policy has a negative effect on shopping rate in retail shops and the dining rate in the restaurants. 

However, the government policy would cause negative influence on economy. As people can not  shopping as normal they did, and they can not dinning in the restaurants. The retail selling growth rate and restaurant revenue growth rate would be reduced, and the economic situation would go worse. 
Corona virus outbreak in Burnie Tasmania (Xuexiao Zhang 538712)
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Model description: 

This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the government which will impact on the local infection and economy. 

 

Assumption:

Government policies will reduce the mobility of the population as well as the infection. In addition, economic activities in the tourism and hospitality industry will suffer negative influences from the government measures. However, essential businesses like supermarkets will benefit from the health policies on the contrary.

 

Variables:

Infection rate, recovery rate, death rate, testing rate are the variables to the cases of Covid-19. On the other hand, the number of cases is also a variable to the government policies, which directly influences the number of exposed. 

 

The GDP is dependent on the variables of economic activities. Nonetheless, the government’s lockdown measure has also become the variable to the economic activities. 

 

Interesting insights:

Government policies are effective to curb infection by reducing the number of exposed when the case number is greater than 10. The economy becomes stagnant when the case spikes up but it climbs up again when the number of cases is under control. 

Sample Model of COVID-19 outbreak in Burnie Tasmania by Yim Fong Ng (544885)
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​BACKGROUND:

The following simulation model demonstrates the relationship between supply, demand and pricing within the real estate and housing world. I have based the model on a small city with a population of 100,000 residents as of 2015. 

AXIS:

X-Axis
The X-Axis shows the time. It begins in 2015 in the month of October and continues for 36 consecutive years. 

Y-Axis
There are 2 Y-Axis on this model. The left hand side relates to the price, demand, and supply, while the right hand side solely lists the population.

As you could see, this town has a population of 100,000 residents to-date. The bottom of the model shows a population loop that produces an exponential growth rate of 2.5%. This dynamic and growing city populates approximately 240,000 residents after 36 years.

MODEL

The model consists of 2 folders named: Buyers/Consumers & Suppliers/Producers. This first folder represents the 'Demand'. It includes a buyers growth rate, buyers interest increase and decrease, a price demand and the demand price. The formulas form an exponential rise in demand due to the rapid and continuous increase in population in this new city. As population increases, so does the demand from buyers. 

The second folder conveys the supply of houses. It includes a sophisticated loop of real estate. Residents who own houses in the market decide to sell the home. This becomes the Houses for sale, also known as the 'supply'. Those houses are sold and the sold houses re-enter the market and the loop continues. 

The supply has an inverse relationship with the price. When prices drop, supplies drop because the demand goes up. And when the price goes up, so does the supply. This will represent the growth of new houses in the market. 

PRICE

Note: The price is based on monthly rent rates.

The price is dependant on many variables. Most importantly, the supply and demand. It also includes factors such as expectations & the economic value of the house. I have included a stable, 'good' economic value for all homes as this fictional town is in a stable and growing area.

Price fluctuates throughout the entire simulation, however it also goes up in price. Over the years houses continue to rise in price while they regularly fluctuate. For example, in 2018 (3 years later), the max price for a home was: $4254.7 and min price was: $852.98. On the other hand, in October 2051 (36 years later), the max price was: $14906 and the min price was: $7661. (This is based on the following data: Houses for Sale: 500, Houses that have sold: 100, Houses in the Market: 730).

SLIDERS

There are 3 sliders on the bottom that could be altered. The simulation would react accordingly. The 3 sliders include changeable data on:
- Houses for Sale.
- Houses that have Sold.
- Houses in the Market.


Real Estate Simulation Assignment - Mitchell Bassil 43290264
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Causal loop representations of macroeconomics taken from the System Dynamics literature contrasted with Forrester's main analysis of social and business organization layers See also Saeed's Forrester Economics IM-183285
Macroeconomics causal loop diagrams
7 10 months ago
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Model description:
This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania, death cases, the governmental responses and Burnie local economy. 

More importantly, the impact of governmental responses to both Covid-19 infection and to local economy, the impact of death cases to local economy are illustrated. 

The model is based on SIR (Susceptible, Infected and recovered) model. 

Variables:
The simulation takes into account the following variables: 

Variables related to Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate. 

Variables related to Governmental policies: (1): Vaccination mandate. (2): Travel restriction to Burnie. (3): Economic support. (4): Gathering restriction.

Variables related to economic growth: Economic growth rate. 

Adjustable variables are listed in the part below, together with the adjusting range.

Assumptions:
(1): Governmental policies are aimed to control(reduce) Covid-19 infections and affect (both reduce and increase) economic growth accordingly.

(2) Governmental policy will only be applied when reported cases are 10 or more. 

(3) The increasing cases will negatively influence Burnie economic growth.

Enlightening insights:
(1) Vaccination mandate, when changing from 80% to 100%, doesn't seem to affect the number of death cases.

(2) Governmental policies are effectively control the growing death cases and limit it to 195. 

Burnie Tasmania Covid - 19 outbreak simulation Model by Yankang Huang 541 277
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No economy can function well without adequate funding and in the absence of finance will eventually fall into recession. Funds (financial assets in the model) are primarily injected through investments. This is certainly true for investments and payments undertaken by the government but also for private investments via bank loans. Net exports (i.e.trade surpluses) also represent an injecton of financial assets into the economy. By contrast financial assets are taken out of the economy through taxation, the repayment of bank loans and the running of a negative trade balance. Also, if the population in aggregate decides to save more this has the effect as if money were taken out of the economy. I have deliberately avoided specifying where the funds for treasury payments and public investments come from, as this is controversial. Modern Monetary Theory, for instance, says that these funds are not provided through tax revenue. Austerity can be seen as a process that deliberately diminishes or takes out financial assets from the economy through taxation, restrictions on bank loans or cutbacks in payments and public spending by the government. It is probably useful to look at insights 2740 and 2741 before examining this CLD because they provide the context and purpose for net public spending and investment.


Investment and Economic Activity
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Crusoe economics test
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Based on 2023 framework from Australian Treasury mapped into the Salutogenesis framework via social wellbeing
Measuring What Matters Framework
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Goodwin Model:
This is a basic version of the Goodwin Model based on Kaoru Yamagushi (2013), Money and Macroeconomic Dynamics, Chapter 4.5 (link)

Equilibrium conditions:
  • Labor Supply = 100
Devation from the equilibrium conditions generates growth cycles.
Goodwin Model
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周末作业
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ESI6550 Group 6
10 months ago
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System Thinking and Modelling of Brgy. Irawan, PPC (Biophysical, Cultural and Economic Component)
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Investigations into the relationships responsible for the success and failure of nations. This investigation was prompted after reading numerous references on the subject and perceiving that *Why Nations Fail: The Origins of Power, Prosperity, and Poverty* by Acemoglu and Robinson seem to make a great deal of sense.
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Why Nations Fail
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SFR23 Scenario 1
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this model shows the relationship between economic growth and government debt (just the bailout debt) and the mortgage default burden. At the current rates, the debt will never be paid off.
bailout debt, mortgage defaults and economic growth
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Base_economics
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Spending by the government creates its own 'financial resource' as the process of crediting an account in the private sector takes place. This may sound like nonsense, but in fact it is 'monetary reality'. This premise is supported by Bell (1998; 2000) and Wray (1998a) who argue that the Treasury does not need to collect or borrow funds in order to spend, but crates new funds as it spends.

Perhaps the following thought experiment  helps to understand how this is possible.  

If you imagine two drawers, each representing an account. The first drawer contains 100 gold coins and the second is empty. Also imagine that there are no other gold coins available at this time. Let's call the first drawer account A and the second account B. Now if you want to transfer 30 gold coins from account A to account B, you would actually first have to take the coins out of drawer A and then place them into drawer B. Account A will then necessarily have 30 coins less in it. Now imagine accounts A and B are held in a computer as electronic money. Instead of 100 gold coins, account A only contains the computer generated number '100'  and account B shows '0'. To get account B to show a balance of '30', it would now simple be necessary to change the '0' to '30' on the computer. The need to raid account A and to take '30' from the number '100' before you could credit  account B does not exist. Money is created as it is entered in B's account irrespective of whether A's account is debited before or after this process or not at
Monetary Reality